arrufat
commented
1 year ago There is an approximate nearest neighbor already in dlib: http://dlib.net/graph_tools.html#find_approximate_k_nearest_neighbors.
However, I think you can reduce the complexity by not storing all the faces. When a new face is detected, if it's already close to any existing face, you don't need to store it. That will reduce the number of faces to compare by a large amount. Then, it's up to you to decide what “near” means in your case.
rajhlinux
dlib-issue-bot
Is it logical to use approximate nearest neighbor algo for dlib's face recognition?
So I have been reading how face recognition works, it seems that approximate nearest neighbor algo is great for large data sets of image vectors as compared to k-means algo.
So for face clustering and image recognition I was wondering if it would make sense to spend the time to actually have dlib to use approximate nearest neighbor algo searching through a real time expanding image vector data set.
Basically making a homemade DVR which runs 24/7 and stores faces and automatically randomly generates labels for them and when new faces are detected it will be stored to database for future reference.
So dlib will constantly need to search through the face database for every face it detects and searching through a large dataset of millions or billions of images, approximate nearest neighbor algo seems to work better since it is much faster searching for possible matches as compared to k-means algo.
There are some great approximate nearest neighbor frameworks, such as "annoy" and "faiss" in c++ on github.
Before I jump into this rabbit hole, have anyone put thought into the same issue for performance and speed in searching through a large and expanding database of image vectors for face recognition and concluded that a-nn(approximate nearest neighbor) is the way to go?
If Spotify and facebook uses a-nn, it seems that dlib would also benefit from it as well for face recognition.
If a-nn is workable with dlib and makes sense to do so, what are some steps I first need to look into for getting this done?
I have been searching this on google and I only find python implementations of using a-nn for face recognition and it does not help to do it in C++ for me to understand how things are working, the code is too short and high level and have no idea what is going on.
Thanks.